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Sensitivity of the Simulation of Tropical Cyclone Size to Microphysics Schemes


doi: 10.1007/s00376-016-5183-2

  • The sensitivity of the simulation of tropical cyclone (TC) size to microphysics schemes is studied using the Advanced Hurricane Weather Research and Forecasting Model (WRF). Six TCs during the 2013 western North Pacific typhoon season and three mainstream microphysics schemes-Ferrier (FER), WRF Single-Moment 5-class (WSM5) and WRF Single-Moment 6-class (WSM6)-are investigated. The results consistently show that the simulated TC track is not sensitive to the choice of microphysics scheme in the early simulation, especially in the open ocean. However, the sensitivity is much greater for TC intensity and inner-core size. The TC intensity and size simulated using the WSM5 and WSM6 schemes are respectively higher and larger than those using the FER scheme in general, which likely results from more diabatic heating being generated outside the eyewall in rainbands. More diabatic heating in rainbands gives higher inflow in the lower troposphere and higher outflow in the upper troposphere, with higher upward motion outside the eyewall. The lower-tropospheric inflow would transport absolute angular momentum inward to spin up tangential wind predominantly near the eyewall, leading to the increment in TC intensity and size (the inner-core size, especially). In addition, the inclusion of graupel microphysics processes (as in WSM6) may not have a significant impact on the simulation of TC track, intensity and size.
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  • Brutsaert W., 1975: A theory for local evaporation (or heat transfer) from rough and smooth surfaces at ground level. Water Resour. Res.,11, 543-550, doi: 10.1029/WR011i004p00543.10.1029/WR011i004p005436ba7d13fa2f1ded764ed31f1ca4021a0http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2FWR011i004p00543%2Ffullhttp://onlinelibrary.wiley.com/doi/10.1029/WR011i004p00543/fullA model proposed earlier (Brutsaert, 1965) for evaporation as a molecular diffusion process into a turbulent atmosphere is extended by joining it with the similarity models for turbulent transfer in the surface sublayer. The assumed mechanisms were suggested by available flow visualization studies near smooth and rough walls; the theoretical result is in good agreement with available experimental evidence. The important dimensionless parameters governing the phenomenon near the surface are the Dalton (or Stanton) number (i.e., mass transfer coefficient), the drag coefficient (u/U), the roughness Reynolds number (uz/v) (except for smooth surfaces), and the Schmidt (or Prandtl) number (v/k). The proposed formulation allows the evaluation of the effects of some parameters, such as surface roughness or molecular diffusivity, that were hitherto not well understood. An important practical result is that in contrast to the drag coefficient, the Dalton number is relatively insensitive to changes in roughness length Z.
    Bu Y. P., R. G. Fovell, and K. L. Corbosiero, 2014: Influence of cloud-radiative forcing on tropical cyclone structure. J. Atmos. Sci.,71, 1644-1662, doi: 10.1175/JAS-D-13-0265.1.10.1175/JAS-D-13-0265.1b74b87d55ff774b4b7ac99c80a4529c1http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2014JAtS...71.1644Bhttp://adsabs.harvard.edu/abs/2014JAtS...71.1644BNot Available
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    Chan K. T. F., J. C. L. Chan, 2012: Size and strength of tropical cyclones as inferred from QuikSCAT data. Mon. Wea. Rev.,140, 811-824, doi: 10.1175/MWR-D-10-05062.1.10.1175/MWR-D-10-05062.13d945e6d85dd94bb9f50d144e35dbb63http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2012MWRv..140..811Chttp://adsabs.harvard.edu/abs/2012MWRv..140..811CNot Available
    Chan K. T. F., J. C. L. Chan, 2013: Angular momentum transports and synoptic flow patterns associated with tropical cyclone size change. Mon. Wea. Rev.,141, 3985-4007, doi: 10.1175/MWR-D-12-00204.1.10.1175/MWR-D-12-00204.16a16553eb4d45f5db6002a79214db99bhttp%3A%2F%2Fconnection.ebscohost.com%2Fc%2Farticles%2F91667323%2Fangular-momentum-transports-synoptic-flow-patterns-associated-tropical-cyclone-size-changehttp://connection.ebscohost.com/c/articles/91667323/angular-momentum-transports-synoptic-flow-patterns-associated-tropical-cyclone-size-changeAbstract This paper is the second part of a comprehensive study on tropical cyclone (TC) size. In Part I, the climatology of TC size and strength over the western North Pacific (WNP) and the North Atlantic was established based on the Quick Scatterometer (QuikSCAT) data. In this second part, the mechanisms that are likely responsible for TC size changes are explored through analyses of angular momentum (AM) transports and synoptic flow patterns associated with the TC. Changes in AM transport in the upper and lower troposphere appear to be important factors that affect TC intensity and size, respectively. The change in TC intensity is positively related to the change in the upper-tropospheric AM export, while the change in TC size is positively proportional to the change in the lower-tropospheric AM import. An examination of the synoptic flow patterns associated with WNP TCs suggests that changes in the synoptic flow near the TC are important in determining the change in TC size, with developments of the lower-tropospheric anticyclonic flows (one to the east and one to the west) bordering the TC being favorable for TC growth and a weakening of the subtropical high to the southeast for TC size reduction. A recurving TC tends to grow if the lower-tropospheric westerlies to its west increase. Moreover, a northward TC movement is related to the change in TC size. For example, a higher northward-moving speed is found for a larger TC, which also agrees well with the AM transport concept.
    Chan K. T. F., J. C. L. Chan, 2014: Impacts of initial vortex size and planetary vorticity on tropical cyclone size. Quart. J. Roy. Meteor. Soc.,140, 2235-2248, doi: 10.1002/qj.2292.10.1002/qj.229241e3b915df8534c01cd1acf4ce1f8502http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2Fqj.2292%2Fabstracthttp://onlinelibrary.wiley.com/doi/10.1002/qj.2292/abstractThis is a numerical modelling study to understand how the initial vortex size, which is defined as the azimuthally averaged radius from the tropical cyclone (TC) centre of the 10 m 17 m s 611 wind, and planetary vorticity ( f ) influence TC size change. Results from 16 f -plane experiments in a quiescent environment suggest that both of them are important in determining TC size change. With a given initial intensity and on the same f -plane, an initially larger TC generally has a larger size at a later stage because it has a larger horizontal wind extent and higher winds outside the inner core. The larger vortex therefore possesses higher angular momentum (AM) in the lower troposphere to increase its size in the outer-core region through AM transport. However, an initially small TC may not be ‘destined’ to be small during its lifetime, which agrees with the observation that TC size has a positive relationship with TC lifetime. In addition, a vortex can apparently grow by itself in a resting environment through fluxes of AM. A vortex at a higher latitude is also found to be not necessarily larger. Furthermore, size change is controlled to some extent by the lower-tropospheric inertial stability associated with the vortex. Consistent with observations, TC size appears to have a maximum at some optimum latitudinal region (65 25°N in general). All the results agree well with the AM transport concept such that the outer-core symmetric relative AM flux and Coriolis torque in the lower troposphere (especially those at the boundary layer) are important factors that govern size change.
    Chan K. T. F., J. C. L. Chan, 2015a: Global climatology of tropical cyclone size as inferred from QuikSCAT data. Int. J. Climatol.,35, 4843-4848, doi: 10.1002/joc.4307.10.1002/joc.43071f3bd8dfe94b773ea08f37e470b2a752http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2Fjoc.4307%2Fcitedbyhttp://onlinelibrary.wiley.com/doi/10.1002/joc.4307/citedbyNot Available
    Chan K. T. F., J. C. L. Chan, 2015b: Impacts of vortex intensity and outer winds on tropical cyclone size. Quart. J. Roy. Meteor. Soc.,141, 525-537, doi: 10.1002/qj.2374.10.1002/qj.2374dfadbb04e695a73b40d2b2c77b0607e2http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2Fqj.2374%2Fcitedbyhttp://onlinelibrary.wiley.com/doi/10.1002/qj.2374/citedbyThe present study seeks to understand how the initial vortex intensity and outer winds influence tropical cyclone (TC) size, which is defined as the azimuthally averaged radius of the 10 m 17 m swind from the TC centre (17), using a full baroclinic model in a quiescent ‐plane environment. The initial vortex intensity is found to influence the size growth rate in the developing phase of the vortex life cycle. However, when the vortex comes to the mature and/or decaying phase of the vortex life cycle, the initial vortex intensity (ranging between 20 and 40 m sin this study) does not strongly affect TC size. On the other hand, vortex intensification or re‐intensification resulting from inner‐core dynamics is apparently favourable for size growth in most instances. In addition, the lower‐tropospheric outer winds of a vortex (i.e. winds beyond 17; e.g. the environmental flows around the TC) are found to be an important factor governing size change. The outer winds closer to 17 are more effective and can influence the vortex size at an earlier stage, especially if the winds are strong.
    Chavas D. R., K. A. Emanuel, 2010: A QuikSCAT climatology of tropical cyclone size. Geophys. Res. Lett., 37,L18816, doi: 10.1029/2010GL044558.10.1029/2010GL04455890850ae985b1562afe55ea00461bebbchttp%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2010GL044558%2Fabstracthttp://onlinelibrary.wiley.com/doi/10.1029/2010GL044558/abstract[1] QuikSCAT data of near-surface wind vectors for the years 1999–2008 are used to create a climatology of tropical cyclone (TC) size, defined as the radius of vanishing winds. The azimuthally-averaged radius of 12 ms 1 wind ( r 12 ) is calculated for a subset of TCs ( N = 2154) whose centers of circulation were clearly identifiable via subjective analysis of the QuikSCAT-analyzed wind field. The outer radius, r 0 , is determined from r 12 using an outer wind structure model that assumes no deep convection beyond r 12 . The global median values of r 12 and r 0 are 197 km and 423 km, respectively, with statistically significant variation across ocean basins. The global distribution of r 12 is found to be approximately log-normal, the distribution of r 0 is quantitatively much closer to log-normal, and the improvement in fit between r 12 and r 0 is attributed to the combined effect of the nature of the model employed and the paired distributions of r 12 and f . Moreover, the normalization employed by Dean et al. (2009) is found to weaken rather than improve the log-normal fit. Finally, within a given storm, both r 12 and r 0 tend to expand very slowly with time early in the storm lifecycle and then becomes quasi-constant, though significant variance exists across storms.
    Chen S.-H., W.-Y. Sun, 2002: A one-dimensional time dependent cloud model. J. Meteor. Soc. Japan,80, 99-118, doi: 10.2151/jmsj.80.99.10.2151/jmsj.80.992d93b119d0d43306b783d6f640cc5044http%3A%2F%2Fci.nii.ac.jp%2Fnaid%2F130004788414%2Fhttp://ci.nii.ac.jp/naid/130004788414/A one-dimensional prognostic cloud model has been developed for possible use in a Cumulus Parameterization Scheme (CPS). In this model, the nonhydrostatic pressure, entrainment, cloud microphysics, lateral eddy mixing and vertical eddy mixing are included, and their effects are discussed. The inclusion of the nonhydrostatic pressure can (1) weaken vertical velocities, (2) help the cloud develop sooner, (3) help maintain a longer mature stage, (4) produce a stronger overshooting cooling, and (5) approximately double the precipitation amount. The pressure perturbation consists of buoyancy pressure and dynamic pressure, and the simulation results show that both of them are important. We have compared our simulation results with those from Ogura and Takahashi's one-dimensional cloud model, and those from the three-dimensional Weather Research and Forecast (WRF) model. Our model, including detailed cloud microphysics, generates stronger maximum vertical velocity than Ogura and Takahashi's results. Furthermore, the results illustrate that this one-dimensional model is capable of reproducing the major features of a convective cloud that are produced by the three-dimensional model when there is no ambient wind shear.
    Donelan M. A., B. K. Haus, N. Reul, W. J. Plant, M. Stiassnie, H. C. Graber, O. B. Brown, and E. S. Saltzman, 2004: On the limiting aerodynamic roughness of the ocean in very strong winds. Geophys. Res. Lett., 31,L18306, doi: 10.1029/2004 GL019460.10.1029/2004GL01946075ac3ffc0178fe410bb5b345296ed005http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2004GL019460%2Freferenceshttp://onlinelibrary.wiley.com/doi/10.1029/2004GL019460/referencesABSTRACT [1] The aerodynamic friction between air and sea is an important part of the momentum balance in the development of tropical cyclones. Measurements of the drag coefficient, relating the tangential stress (frictional drag) between wind and water to the wind speed and air density, have yielded reliable information in wind speeds less than 20 m/s (about 39 knots). In these moderate conditions it is generally accepted that the drag coefficient (or equivalently, the “aerodynamic roughness”) increases with the wind speed. Can one merely extrapolate this wind speed tendency to describe the aerodynamic roughness of the ocean in the extreme wind speeds that occur in hurricanes (wind speeds greater than 30 m/s)? This paper attempts to answer this question, guided by laboratory extreme wind experiments, and concludes that the aerodynamic roughness approaches a limiting value in high winds. A fluid mechanical explanation of this phenomenon is given.
    Fovell R. G., H. Su, 2007: Impact of cloud microphysics on hurricane track forecasts. Geophys. Res. Lett., 34,L24810, doi: 10.1029/2007GL031723.10.1029/2007GL03172380abb257205dfffd613554a026915df5http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2007GL031723%2Fpdfhttp://onlinelibrary.wiley.com/doi/10.1029/2007GL031723/pdfSimulations of Hurricane Rita (2005) at operational resolutions (30 and 12 km) reveal significant track sensitivity to cloud microphysical details, rivaling variation seen in the National Hurricane Center's multi-model consensus forecast. Microphysics appears to directly or indirectly modulate vortex characteristics including size and winds at large radius and possibly other factors involved in hurricane motion. Idealized simulations made at higher (3 km) resolution help isolate the microphysical influence.
    Fovell R. G., K. L. Corbosiero, and H. C. Kuo, 2009: Cloud microphysics impact on hurricane track as revealed in idealized experiments. J. Atmos. Sci.,66, 1764-1778, doi: 10.1175/ 2008JAS2874.1.10.1175/2008JAS2874.1b370f62b95807875f94d084af93ef610http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2009JAtS...66.1764Fhttp://adsabs.harvard.edu/abs/2009JAtS...66.1764FWith the assistance of some special sensitivity tests, the influence of microphysics and fall speed on radial temperature gradients, leading to different outer wind strengths and tracks, is shown. Among other things, this work demonstrates that the treatment of outer rainbands in operational models can potentially influence how simulated storms move, thus affecting position forecasts.
    Fovell R. G., K. L. Corbosiero, A. Seifert, and K. N. Liou, 2010: Impact of cloud-radiative processes on hurricane track. Geophys. Res. Lett., 37,L07808, doi: 10.1029/2010GL042691.10.1029/2010GL042691ecff25dcf0fb1d2232673e8f17578c0chttp%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2010GL042691%2Fpdfhttp://onlinelibrary.wiley.com/doi/10.1029/2010GL042691/pdfIdealized simulations of tropical cyclones suggest that previously established motion sensitivity to cloud microphysical processes may emerge through cloud-radiative feedback. When commonly employed radiation parameterizations and absorption treatments are used, microphysical schemes generate a variety of tracks, influenced by different, scheme-dependent convective heating patterns and magnitudes. However, these variations nearly vanish when cloud-radiative feedback is neglected, with storms becoming stronger and more compact. This study strongly motivates further research with respect to how condensation particles influence radiative processes and thus storm dynamics and thermodynamics.
    Fudeyasu H., Y. Q. Wang, 2011: Balanced contribution to the intensification of a tropical cyclone simulated in TCM4: Outer core spin-up process. J. Atmos. Sci.,68, 430-449, doi: 10.1175/2010JAS3523.1.96c6d782ab7ccf9aad44a7b8d42dc451http%3A%2F%2Fadsabs.harvard.edu%2Fcgi-bin%2Fnph-data_query%3Fbibcode%3D2011JAtS...68..430F%26db_key%3DPHY%26link_type%3DABSTRACThttp://xueshu.baidu.com/s?wd=paperuri%3A%28ae40618d077511581b39ff5f7fac8db1%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Fadsabs.harvard.edu%2Fcgi-bin%2Fnph-data_query%3Fbibcode%3D2011JAtS...68..430F%26db_key%3DPHY%26link_type%3DABSTRACT&ie=utf-8&sc_us=15792292735242510949
    Goerss J. S., 2000: Tropical cyclone track forecasts using an ensemble of dynamical models. Mon. Wea. Rev.,128, 1187-1193, doi: 10.1175/1520-0493(2000)128<1187:TCTFUA> 2.0.CO;2.10.1175/1520-0493(2000)128<1187:TCTFUA>2.0.CO;212daea6fccc4870af8896d0d518bb8fdhttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2000MWRv..128.1187Ghttp://adsabs.harvard.edu/abs/2000MWRv..128.1187GNot Available
    Han J., H.-L. Pan, 2011: Revision of convection and vertical diffusion schemes in the NCEP Global Forecast System. Wea. Forecasting,26, 520-533, doi: 10.1175/WAF-D-10-05038.1.10.1175/WAF-D-10-05038.1b268077d000babacfc600f4b4b31ac76http%3A%2F%2Fconnection.ebscohost.com%2Fc%2Farticles%2F64842702%2Frevision-convection-vertical-diffusion-schemes-ncep-global-forecast-systemhttp://connection.ebscohost.com/c/articles/64842702/revision-convection-vertical-diffusion-schemes-ncep-global-forecast-systemAbstract A new physics package containing revised convection and planetary boundary layer (PBL) schemes in the National Centers for Environmental Prediction Global Forecast System is described. The shallow convection (SC) scheme in the revision employs a mass flux parameterization replacing the old turbulent diffusion-based approach. For deep convection, the scheme is revised to make cumulus convection stronger and deeper to deplete more instability in the atmospheric column and result in the suppression of the excessive grid-scale precipitation. The PBL model was revised to enhance turbulence diffusion in stratocumulus regions. A remarkable difference between the new and old SC schemes is seen in the heating or cooling behavior in lower-atmospheric layers above the PBL. While the old SC scheme using the diffusion approach produces a pair of layers in the lower atmosphere with cooling above and heating below, the new SC scheme using the mass-flux approach produces heating throughout the convection layers. In particular, the new SC scheme does not destroy stratocumulus clouds off the west coasts of South America and Africa as the old scheme does. On the other hand, the revised deep convection scheme, having a larger cloud-base mass flux and higher cloud tops, appears to effectively eliminate the remaining instability in the atmospheric column that is responsible for the excessive grid-scale precipitation in the old scheme. The revised PBL scheme, having an enhanced turbulence mixing in stratocumulus regions, helps prevent too much low cloud from forming. An overall improvement was found in the forecasts of the global 500-hPa height, vector wind, and continental U.S. precipitation with the revised model. Consistent with the improvement in vector wind forecast errors, hurricane track forecasts are also improved with the revised model for both Atlantic and eastern Pacific hurricanes in 2008.
    Heming J., J. C. L. Chan, and A. M. Radford, 1995: A new scheme for the initialisation of tropical cyclones in the UK Meteorological Office global model. Meteorological Applications,2, 171-184, doi: 10.1002/met.5060020211.10.1002/met.5060020211d944a5914bd1c46bd09d8d1708088ae3http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2Fmet.5060020211%2Fabstracthttp://onlinelibrary.wiley.com/doi/10.1002/met.5060020211/abstractNot Available Not Available
    Hill K. A., G. M. Lackmann, 2009: Influence of environmental humidity on tropical cyclone size. Mon. Wea. Rev.,137, 3294-3315, doi: 10.1175/2009MWR2679.1.10.1175/2009MWR2679.195fd4db69ca7e3032acc79bdc31c2241http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2009MWRv..137.3294Hhttp://adsabs.harvard.edu/abs/2009MWRv..137.3294HObservations demonstrate that the radius of maximum winds in tropical cyclones (TCs) can vary by an order of magnitude; similar size differences are evident in other spatial measures of the wind field as well as in cloud and precipitation fields. Many TC impacts are related to storm size, yet the physical mechanisms that determine TC size are not well understood and have received limited research attention. Presented here is a hypothesis suggesting that one factor controlling TC size is the environmental relative humidity, to which the intensity and coverage of precipitation occurring outside the TC core is strongly sensitive. From a potential vorticity (PV) perspective, the lateral extent of the TC wind field is linked to the size and strength of the associated cyclonic PV anomalies. Latent heat release in outer rainbands can result in the diabatic lateral expansion of the cyclonic PV distribution and balanced wind field. Results of idealized numerical experiments are consistent with the hypothesized sensitivity of TC size to environmental humidity. Simulated TCs in dry environments exhibit reduced precipitation outside the TC core, a narrower PV distribution, and reduced lateral extension of the wind field relative to storms in more moist environments. The generation of diabatic PV in spiral bands is critical to lateral wind field expansion in the outer portion of numerically simulated tropical cyclones. Breaking vortex Rossby waves in the eyewall lead to an expansion of the eye and the weakening of inner-core PV gradients in the moist environment simulation. Feedback mechanisms involving surface fluxes and the efficiency of diabatic PV production with an expanding cyclonic wind field are discussed.
    Hong S.-Y., J.-O. J. Lim, 2006: The WRF Single-Moment 6-Class Microphysics Scheme (WSM6). Journal of the Korean Meteorological Society, 42, 129- 151.7308c59e0fe08d8147ff5b2869261e63http%3A%2F%2Fwww.dbpia.co.kr%2FJournal%2FArticleDetail%2F773025http://www.dbpia.co.kr/Journal/ArticleDetail/773025This study examines the performance of the Weather Research and Forecasting (WRF)-Single-Moment- Microphysics scheme (WSMMPs) with a revised ice-microphysics of the Hong et al. In addition to the simple (WRF Single-Moment 3-class Microphysics scheme; WSM3) and mixed-phase (WRF Single-Moment 5-class Microphysics scheme; WSM5) schemes of the Hong et al., a more complex scheme with the inclusion of graupel as another predictive variable (WRF Single-Moment 6-class Microphysics scheme; WSM6) was developed. The characteristics of the three categories of WSMMPs were examined for an idealized storm case and a heavy rainfall event over Korea. In an idealized thunderstorm simulation, the overall evolutionary features of the storm are not sensitive to the number of hydrometeors in the WSMMPs; however, the evolution of surface precipitation is significantly influenced by the complexity in microphysics. A simulation experiment for a heavy rainfall event indicated that the evolution of the simulated precipitation with the inclusion of graupel (WSM6) is similar to that from the simple (WSM3) and mixed-phase (WSM5) microphysics in a low-resolution grid; however, in a high-resolution grid, the amount of rainfall increases and the peak intensity becomes stronger as the number of hydrometeors increases.
    Hong S.-Y., J. Dudhia, and S.-H. Chen, 2004: A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon. Wea. Rev.,132, 103-120, doi: 10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO; 2.10.1175/1520-0493(2004)1322.0.CO;27913d9ed85b1a9bbcdcb88db96a17cbbhttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2004MWRv..132..103Hhttp://adsabs.harvard.edu/abs/2004MWRv..132..103HNot Available
    Hong S.-Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev.,134, 2318-2341, doi: 10.1175/MWR3199.1.10.1175/MWR3199.179f98ee85a3853a6bfee0ec84e90c901http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2006MWRv..134.2318Hhttp://adsabs.harvard.edu/abs/2006MWRv..134.2318HThis paper proposes a revised vertical diffusion package with a nonlocal turbulent mixing coefficient in the planetary boundary layer (PBL). Based on the study of Noh et al. and accumulated results of the behavior of the Hong and Pan algorithm, a revised vertical diffusion algorithm that is suitable for weather forecasting and climate prediction models is developed. The major ingredient of the revision is the inclusion of an explicit treatment of entrainment processes at the top of the PBL. The new diffusion package is called the Yonsei University PBL (YSU PBL). In a one-dimensional offline test framework, the revised scheme is found to improve several features compared with the Hong and Pan implementation. The YSU PBL increases boundary layer mixing in the thermally induced free convection regime and decreases it in the mechanically induced forced convection regime, which alleviates the well-known problems in the Medium-Range Forecast (MRF) PBL. Excessive mixing in the mixed layer in the presence of strong winds is resolved. Overly rapid growth of the PBL in the case of the Hong and Pan is also rectified. The scheme has been successfully implemented in the Weather Research and Forecast model producing a more realistic structure of the PBL and its development. In a case study of a frontal tornado outbreak, it is found that some systematic biases of the large-scale features such as an afternoon cold bias at 850 hPa in the MRF PBL are resolved. Consequently, the new scheme does a better job in reproducing the convective inhibition. Because the convective inhibition is accurately predicted, widespread light precipitation ahead of a front, in the case of the MRF PBL, is reduced. In the frontal region, the YSU PBL scheme improves some characteristics, such as a double line of intense convection. This is because the boundary layer from the YSU PBL scheme remains less diluted by entrainment leaving more fuel for severe convection when the front triggers it.
    Iacono M. J., J. S. Delamere, E. J. Mlawer, M. W. Shephard, S. A. Clough, and W. D. Collins, 2008: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., 113,D13103, doi: 10.1029/2008JD009944.10.1029/2008JD0099440b25c1c2a104d51c498700a19269e7f0http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2008JD009944%2Ffullhttp://onlinelibrary.wiley.com/doi/10.1029/2008JD009944/fullA primary component of the observed, recent climate change is the radiative forcing from increased concentrations of long-lived greenhouse gases (LLGHGs). Effective simulation of anthropogenic climate change by general circulation models (GCMs) is strongly dependent on the accurate representation of radiative processes associated with water vapor, ozone and LLGHGs. In the context of the increasing application of the Atmospheric and Environmental Research, Inc. (AER) radiation models within the GCM community, their capability to calculate longwave and shortwave radiative forcing for clear sky scenarios previously examined by the radiative transfer model intercomparison project (RTMIP) is presented. Forcing calculations with the AER line-by-line (LBL) models are very consistent with the RTMIP line-by-line results in the longwave and shortwave. The AER broadband models, in all but one case, calculate longwave forcings within a range of -0.20 to 0.23 W m{sup -2} of LBL calculations and shortwave forcings within a range of -0.16 to 0.38 W m{sup -2} of LBL results. These models also perform well at the surface, which RTMIP identified as a level at which GCM radiation models have particular difficulty reproducing LBL fluxes. Heating profile perturbations calculated by the broadband models generally reproduce high-resolution calculations within a few hundredths K d{sup more -1} in the troposphere and within 0.15 K d{sup -1} in the peak stratospheric heating near 1 hPa. In most cases, the AER broadband models provide radiative forcing results that are in closer agreement with high 20 resolution calculations than the GCM radiation codes examined by RTMIP, which supports the application of the AER models to climate change research. less
    Jimènez, P. A., J. Dudhia, J. F. González-Rouco, J. Navarro, J. P. Montávez, E. Garcá-Bustamante, 2012: A revised scheme for the WRF surface layer formulation. Mon. Wea. Rev.,140, 898-918, doi: 10.1175/MWR-D-11-00056.1.10.1175/MWR-D-11-00056.15f073a65af49b2be446420bb683c566chttp%3A%2F%2Fonlinelibrary.wiley.com%2Fresolve%2Freference%2FXREF%3Fid%3D10.1175%2FMWR-D-11-00056.1http://onlinelibrary.wiley.com/resolve/reference/XREF?id=10.1175/MWR-D-11-00056.1Abstract This study summarizes the revision performed on the surface layer formulation of the Weather Research and Forecasting (WRF) model. A first set of modifications are introduced to provide more suitable similarity functions to simulate the surface layer evolution under strong stable/unstable conditions. A second set of changes are incorporated to reduce or suppress the limits that are imposed on certain variables in order to avoid undesired effects (e.g., a lower limit in u * ). The changes introduced lead to a more consistent surface layer formulation that covers the full range of atmospheric stabilities. The turbulent fluxes are more (less) efficient during the day (night) in the revised scheme and produce a sharper afternoon transition that shows the largest impacts in the planetary boundary layer meteorological variables. The most important impacts in the near-surface diagnostic variables are analyzed and compared with observations from a mesoscale network.
    Kain J., 2004: The Kain-Fritsch convective parameterization: An update. J. Appl. Meteor.,43, 170-181, doi: 10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2.10.1175/1520-0450(2004)04360;0170:tkcpau62;2.0.co;29b75490262b7749ec91d527514242feahttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2004japme..43..170khttp://adsabs.harvard.edu/abs/2004japme..43..170kNumerous modifications to the Kain Fritsch convective parameterization have been implemented over the last decade. These modifications are described, and the motivating factors for the changes are discussed. Most changes were inspired by feedback from users of the scheme (primarily numerical modelers) and interpreters of the model output (mainly operational forecasters). The specific formulation of the modifications evolved from an effort to produce desired effects in numerical weather prediction while also rendering the scheme more faithful to observations and cloud-resolving modeling studies.
    Kessler E., 1995: On the continuity and distribution of water substance in atmospheric circulations. Atmospheric Research,38, 109-145, doi: 10.1016/0169-8095(94)00090-Z.10.1016/0169-8095(94)00090-Ze287cf06f7cc4d6418bca5b1aff67851http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2F016980959400090Zhttp://www.sciencedirect.com/science/article/pii/016980959400090ZThe studies show the nature of probable connections among distributions of water vapor, cloud, rain, and snow with vertical and horizontal winds, divergence of the wind, compressibility of the atmosphere, and the strength and distribution of various microphysical processes. The findings also aid interpretation of observations and they offer lessons for efforts toward artificial augmentation of precipitation.
    Kimball S. K., M. S. Mulekar, 2004: A 15-year climatology of North Atlantic tropical cyclones. Part I: Size parameters. J. Climate,17, 3555-3575, doi: 10.1175/1520-0442(2004)017 <3555:AYCONA>2.0.CO;2.10.1175/1520-0442(2004)0172.0.CO;284431789080b1218c2fcd6197890683fhttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2004JCli...17.3555Khttp://adsabs.harvard.edu/abs/2004JCli...17.3555KThe extended best-track (EBT) dataset combines the information contained in the tropical cyclone best-track dataset with measurements of tropical cyclone “size parameters.” These parameters include the radii of the eye (REYE), maximum winds (RMW), gale-force winds (or size; 17.5 m s; R17), damaging-force winds (25.7 m s; R26), hurricane-force winds (32.9 m s; R33), and the outermost closed isobar (ROCI). The latest update of this dataset, to be used in this study for a size parameter climatology, contains the size parameters for North Atlantic tropical cyclones from 1988 to 2002. Such a climatology has not yet been established in this basin. Most of the results of this North Atlantic study agree with documented tropical cyclone theory and results from similar studies of northwest Pacific tropical cyclones. This provides confidence that the observations of the size parameters in the dataset are reliable. Furthermore, data west and east of 55°W (the boundary beyond which no aircraft observations are made) are compared. Some differences occur in some of the size parameters, but the sample west of 55°W is significantly larger and displays a greater spread. This provides confidence that the total dataset may not be affected by the nonaircraft data east of 55°W. The spatial and temporal distribution of the size parameters is investigated. The radii of gale-force (R17), damaging-force (R26), and hurricane-force (R33) winds tend to increase as storms move poleward and westward. North of 40°N, R33 and R26 decrease, while R17 increases. This is a reflection of storm weakening after recurvature. Gulf of Mexico storms have larger ROCIs but smaller eyes, R33s, R26s, and R17s than North Atlantic storms between 50° and 80°W. Gulf systems tend to form in the gulf instead of moving into this area from the Atlantic. Gulf incipient systems are likely to be tropical upper-tropospheric trough (TUTT) cells or monsoon trough features from the eastern Pacific instead of easterly waves from Africa. Early-season storms tend to be small; late-season storms are larger; and storm size peaks in September. Weakening storms tend to have smaller eyes than intensifying storms; most weakening storms are intense systems that have reached the end of their intensification and eyewall contraction process. These highly organized systems take a long time to spin down. Weak systems with large eyes take a long time to get organized and require a long time to intensify. Knowledge of the areal extent of damaging winds will provide forecasters and emergency managers with additional information to assess the damage potential of approaching storms.
    Knaff J. A., S. P. Longmore, and D. A. Molenar, 2014: An objective satellite-based tropical cyclone size climatology. J. Climate,27, 455-476, doi: 10.1175/JCLI-D-13-00096.1.10.1175/JCLI-D-13-00096.1dd1d8f2b980416ad90e2c3877735565ehttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2014JCli...27..455Khttp://adsabs.harvard.edu/abs/2014JCli...27..455KNot Available
    Krishnamurti T. N., R. Correa-Torres G. Rohaly, and D. Oosterhof, 1997: Physical initialization and hurricane ensemble forecasts. Wea. Forecasting,12, 503-514, doi: 10.1175/1520-0434(1997)012<0503:PIAHEF>2.0.CO;2.10.1175/1520-0434(1997)012<0503:PIAHEF>2.0.CO;2ed106b0a004bdc0e774db63b12e1fbbchttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1997WtFor..12..503Khttp://adsabs.harvard.edu/abs/1997WtFor..12..503KAbstract Ensemble forecasting of hurricane tracks is an emerging area in numerical weather prediction. In this paper, the spread of the ensemble of forecast tracks from a family of different First Global GARP (Global Atmospheric Research Program) Experiment analyses is illustrated. All forecasts start at the same date and use the same global prediction model. The authors have examined ensemble forecasts for three different hurricanes/typhoons of the year 1979. The authors have used eight different initial analyses to examine the spread of ensemble forecasts through 6 days from the initial state. A total of 16 forecasts were made, of which 8 of them invoked physical initialization. Physical initialization is a procedure for improving the initial rainfall rates consistent with satellite/rain gauge based measures of rainfall. The main results of this study are that useful track forecasts are obtained from physical initialization, which is shown to suppress the spread of the ensemble of track forecasts. The spread of the tracks is quite large if the rain rates are not initialized. The major issue here is how one could make use of this information on ensemble forecasts for providing guidance. Toward that end, a statistical framework that makes use of the spread of forecast tracks to provide such guidance is presented.
    Kurihara Y., M. A. Bender, R. E. Tuleya, and R. J. Ross, 1990: Prediction experiments of Hurricane Gloria (1985) using a multiply nested movable mesh model. Mon. Wea. Rev.,118, 2185-2198, doi: 10.1175/1520-0493(1990)118<2185: PEOHGU>2.0.CO;2.10.1175/1520-0493(1990)1182.0.CO;2b4dfd3604e01129a75302aaa1e2b3e79http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1990MWRv..118.2185Khttp://adsabs.harvard.edu/abs/1990MWRv..118.2185KNot Available
    Leslie L. M., G. J. Holland.1995: On the bogussing of tropical cyclones in numerical models: A comparison of vortex profiles. Meteor. Atmos. Phys.,56, 101-110, doi: 10.1007/ BF01022523.10.1007/BF01022523197c23fb643ca84a82214bce769a61e2http%3A%2F%2Frd.springer.com%2Farticle%2F10.1007%2FBF01022523http://rd.springer.com/article/10.1007/BF01022523At the resolutions currently in use, and with the sparse oceanic data coverage, numerical analyses cannot adequately represent tropical cyclone circulations for use in numerical weather prediction models. In many cases there is no circulation present at all. Most numerical weather prediction centers therefore employ a “bogussing” scheme to force a tropical cyclone vortex into the numerical analysis. The standard procedure is to define a synthetic data distribution based on an analytically prescribed vortex, which is passed to the analysis scheme as a set of high quality observations.
    Leslie L. M., J. F. Le Marshall, R. P. Morison, C. Spinoso, R. J. Purser, N. Pescod, and R. Seecamp, 1998: Improved hurricane track forecasting from the continuous assimilation of high quality satellite wind data. Mon. Wea. Rev.,126, 1248-1257, doi: 10.1175/1520-0493(1998)126<1248:IHTFFT>2. 0.CO;2.10.1175/1520-0493(1998)1262.0.CO;2a65b5f1ebcf3eba67a9214746d0e87b2http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1998MWRv..126.1248Lhttp://adsabs.harvard.edu/abs/1998MWRv..126.1248LNot Available
    Li Q. Q., Y. Q. Wang, and Y. H. Duan, 2014: Effects of diabatic heating and cooling in the rapid filamentation zone on structure and intensity of a simulated tropical cyclone. J. Atmos. Sci.,71, 3144-3163, doi: 10.1175/JAS-D-13-0312.1.10.1175/JAS-D-13-0312.1028f128628fbbdf06b3a1bee3822dadfhttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2014JAtS...71.3144Lhttp://adsabs.harvard.edu/abs/2014JAtS...71.3144LThe effects of diabatic heating and cooling in the rapid filamentation zone (RFZ), within which inner rainbands are often active, on tropical cyclone (TC) structure and intensity are investigated based on idealized numerical experiments using a cloud-resolving TC model (TCM4). The results show that removal of heating (cooling) in the RFZ would reduce (increase) the TC intensity. Diabatic heating in the RFZ plays an important role in increasing the inner-core size whereas diabatic cooling tends to limit the inner-core size increase or even reduce the inner-core size of a TC. Removal of both diabatic heating and cooling in the RFZ greatly suppresses the activity of inner rainbands but leads to the quasi-periodic development of a convective ring immediately outside of the inner core. A similar convective ring also develops in an experiment with the removal of diabatic heating only in the RFZ. With diabatic cooling removed only in the RFZ, an annular-hurricane-like structure arises with the outer rainbands largely suppressed.
    Li Q. Q., Y. Q. Wang, and Y. H. Duan, 2015: Impacts of evaporation of rainwater on tropical cyclone structure and intensity-A revisit. J. Atmos. Sci.,72, 1323-1345, doi: 10.1175/JAS-D-14-0224.1.10.1175/JAS-D-14-0224.109daf698d80dd1f1ccb2d0754ff314c3http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2015JAtS...72.1323Lhttp://adsabs.harvard.edu/abs/2015JAtS...72.1323LAbstract The impact of evaporation of rainwater on tropical cyclone (TC) intensity and structure is revisited in this study. Evaporative cooling can result in strong downdrafts and produce lowquivalent potential temperature air in the inflow boundary layer, particularly in the region outside the eyewall, significantly suppressing eyewall convection and reducing the final intensity of a TC. Different from earlier findings, results from this study show that outer rainbands still form but are short lived in the absence of evaporation. Evaporation of rainwater is shown to facilitate the formation of outer rainbands indirectly by reducing the cooling due to melting of ice particles outside the inner core, not by the cold-pool dynamics, as previously believed. Only exclusion of evaporation in the eyewall region or the rapid filamentation zone has a very weak effect on the inner-core size change of a TC, whereas how evaporation in the outer core affects the inner-core size depends on how active the inner rainbands are. More (less) active inner rainbands may lead to an increase (a decrease) in the inner-core size.
    Li X. L., Z. X. Pu, 2008: Sensitivity of numerical simulation of early rapid intensification of hurricane Emily (2005) to cloud microphysical and planetary boundary layer parameterizations. Mon. Wea. Rev.,136, 4819-4838, doi: 10.1175/2008 MWR2366.1.b2635a44812783616b707ddcc8ecfce3http%3A%2F%2Fadsabs.harvard.edu%2Fcgi-bin%2Fnph-data_query%3Fbibcode%3D2008MWRv..136.4819L%26db_key%3DPHY%26link_type%3DABSTRACThttp://xueshu.baidu.com/s?wd=paperuri%3A%280d02313907ba8518c91d21d7cf2533ba%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Fadsabs.harvard.edu%2Fcgi-bin%2Fnph-data_query%3Fbibcode%3D2008MWRv..136.4819L%26db_key%3DPHY%26link_type%3DABSTRACT&ie=utf-8&sc_us=6076612326383859248
    Lin Y.-L., R. D. Farley, and H. D. Orville, 1983: Bulk parameterization of the snow field in a cloud model. J. Climate Appl. Meteor.,22, 1065-1092, doi: 10.1175/1520-0450(1983)022 <1065:BPOTSF>2.0.CO;2.10.1175/1520-0450(1983)022<1065:BPOTSF>2.0.CO;29190891c3775ec6ca868fe681504eba0http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1983japme..22.1065lhttp://adsabs.harvard.edu/abs/1983japme..22.1065lA two-dimensional, time-dependent cloud model has been used to simulate a moderate intensity thunderstorm for the High Plains region. Six forms of water substance (water vapor, cloud water, cloud ice, rain, snow and hail, i.e., graupel) are simulated. The model utilizes the `bulk water' microphysical parameterization technique to represent the precipitation fields which are all assumed to follow exponential size distribution functions. Autoconversion concepts are used to parameterize the collision-coalescence and collision-aggregation processes. Accretion processes involving the various forms of liquid and solid hydrometeors are simulated in this model. The transformation of cloud ice to snow through autoconversion (aggregation) and Bergeron process and subsequent accretional growth or aggregation to form hail are simulated. Hail is also produced by various contact mechanisms and via probabilistic freezing of raindrops. Evaporation (sublimation) is considered for all precipitation particles outside the cloud. The melting of hail and snow are included in the model. Wet and dry growth of hail and shedding of rain from hail are simulated.The simulations show that the inclusion of snow has improved the realism of the results compared to a model without snow. The formation of virga from cloud anvils is now modeled. Addition of the snow field has resulted in the inclusion of more diverse and physically sound mechanisms for initiating the hail field, yielding greater potential for distinguishing dominant embryo types characteristically different from warm- and cold-based clouds.
    Liu K. S., J. C. L. Chan, 2002: Synoptic flow patterns associated with small and large tropical cyclones over the western North Pacific. Mon. Wea. Rev.,130, 2134-2142, doi: 10.1175/ 1520-0493(2002)130<2134:SFPAWS>2.0.CO;2.a504fb0067cdf035698df88c4abda418http%3A%2F%2Fadsabs.harvard.edu%2Fcgi-bin%2Fnph-data_query%3Fbibcode%3D2002MWRv..130.2134L%26db_key%3DPHY%26link_type%3DABSTRACThttp://xueshu.baidu.com/s?wd=paperuri%3A%28e83bcba6e09d89dbd5a69b6716996f86%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Fadsabs.harvard.edu%2Fcgi-bin%2Fnph-data_query%3Fbibcode%3D2002MWRv..130.2134L%26db_key%3DPHY%26link_type%3DABSTRACT&ie=utf-8&sc_us=11393737675499491735
    Merrill R. T., 1984: A comparison of large and small tropical cyclones. Mon. Wea. Rev.,112, 1408-1418, doi: 10.1175/1520-0493(1984)112<1408:ACOLAS>2.0.CO;2.10.1175/1520-0493(1984)112<1408:ACOLAS>2.0.CO;240e8fa0679e068737dddb700ed2fa325http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1984MWRv..112.1408Mhttp://adsabs.harvard.edu/abs/1984MWRv..112.1408MNot Available
    Miyoshi T., T. Komori, H. Yonehara, R. Sakai, and M. Yamaguchi, 2010: Impact of resolution degradation of the initial condition on typhoon track forecasts. Wea. Forecasting,25, 1568-1573, doi: 10.1175/2010WAF2222392.1.20cb30bdb050294eb9bfb9a80753e92fhttp%3A%2F%2Fadsabs.harvard.edu%2Fcgi-bin%2Fnph-data_query%3Fbibcode%3D2010WtFor..25.1568M%26db_key%3DPHY%26link_type%3DABSTRACT%26high%3D15332http://xueshu.baidu.com/s?wd=paperuri%3A%286e6cf701d8fa03e2ec9436fd480d2bb3%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Fadsabs.harvard.edu%2Fcgi-bin%2Fnph-data_query%3Fbibcode%3D2010WtFor..25.1568M%26db_key%3DPHY%26link_type%3DABSTRACT%26high%3D15332&ie=utf-8&sc_us=13589413727546087348
    Rappaport, E. N., Coauthors, 2009: Advances and challenges at the National Hurricane Center. Wea. Forecasting,24, 395-419, doi: 10.1175/2008WAF2222128.1.10.1175/2008WAF2222128.14d87fc2a18c68ff8a54160435ca8b554http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2009WtFor..24..395Rhttp://adsabs.harvard.edu/abs/2009WtFor..24..395RThe National Hurricane Center issues analyses, forecasts, and warnings over large parts of the North Atlantic and Pacific Oceans, and in support of many nearby countries. Advances in observational capabilities, operational numerical weather prediction, and forecaster tools and support systems over the past 15–20 yr have enabled the center to make more accurate forecasts, extend forecast lead times, and provide new products and services. Important limitations, however, persist. This paper discusses the current workings and state of the nation’s hurricane warning program, and highlights recent improvements and the enabling science and technology. It concludes with a look ahead at opportunities to address challenges.
    Rogers E., T. Black, B. Ferrier, Y. Lin, D. Parrish, and G. DiMego, 2001: Changes to the NCEP Meso Eta Analysis and Forecast System: Increase in resolution,new cloud microphysics, modified precipitation assimilation, modified 3DVAR analysis. [Available online at .]http://www.emc.ncep.noaa.gov/mmb/mmbpll/eta12tpb/
    Rogers, R., Coauthors, 2006: The intensity forecasting experiment: A NOAA multiyear field program for improving tropical cyclone intensity forecasts. Bull. Amer. Meteor. Soc.,87, 1523-1537, doi: 10.1175/BAMS-87-11-1523.10.1175/BAMS-87-11-15238dfdac8065a459388c37a5b5964c55b7http%3A%2F%2Fconnection.ebscohost.com%2Fc%2Farticles%2F25151656%2Fintensity-forecasting-experimenthttp://connection.ebscohost.com/c/articles/25151656/intensity-forecasting-experimentThe article describes a U.S. National Oceanic and Atmospheric Administration (NOAA) multiyear field program called "Intensity Forecasting Experiment" designed to improve the forecasting of tropical cyclone intensity in the Atlantic and East Pacific basins. Graphs present annually averaged official NOAA National Hurricane Center (NHC) forty-eight-hour forecast errors for tropical cyclones. The Experiment is taking a novel approach to the development of forecast abilities, the testing of real-time observational capabilities, and development of a physical understanding of tropical cyclones.
    Skamarock, W. C., Coauthors, 2008: A description of the Advanced Research WRF version 3. NCAR Tech. Note NCAR/ TN-4751STR,113 pp. [Available online at .]http://www2.mmm.ucar.edu/wrf/users/docs/arw_v3.pdf
    Smith R. K., C. W. Schmidt, and M. T. Montgomery, 2011: An investigation of rotational influences on tropical-cyclone size and intensity. Quart. J. Roy. Meteor. Soc.,137, 1841-1855, doi: 10.1002/qj.862.10.1002/qj.8627e0fa3f80cea3b08dc92c26e3c75708chttp%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2Fqj.862%2Fpdfhttp://onlinelibrary.wiley.com/doi/10.1002/qj.862/pdfNot Available
    Srinivas C. V., R. Venkatesan, D. V. Bhaskar Rao, and D. Hari Prasad, 2007: Numerical simulation of Andhra severe cyclone (2003): Model sensitivity to the boundary layer and convection parameterization. Pure Appl. Geophys.,164, 1465-1487, doi: 10.1007/s00024-007-0228-1.10.1007/s00024-007-0228-1844b92cf6f8582815355d1066a988e09http%3A%2F%2Flink.springer.com%2F10.1007%2Fs00024-007-0228-1http://link.springer.com/10.1007/s00024-007-0228-1The Andhra severe cyclonic storm (2003) is simulated to study its evolution, structure, intensity and movement using the Penn State/NCAR non-hydrostatic mesoscale atmospheric model MM5. The model is used with three interactive nested domains at 81, 27 and 9 km resolutions covering the Bay of Bengal and adjoining Indian Peninsula. The performance of the Planetary Boundary Layer (PBL) and convective parameterization on the simulated features of the cyclone is studied by conducting sensitivity experiments. Results indicate that while the boundary layer processes play a significant role in determining both the intensity and movement, the convective processes especially control the movement of the model storm. The Mellor-Yamada scheme is found to yield the most intensive cyclone. While the combination of Mellor-Yamada (MY) PBL and Kain-Fritsch 2 (KF2) convection schemes gives the most intensive storm, the MRF PBL with KF2 convection scheme produces the best simulation in terms of intensity and track. Results of the simulation with the combination of MRF scheme for PBL and KF2 for convection show the evolution and major features of a mature tropical storm. The model has very nearly simulated the intensity of the storm though slightly overpredicted. Simulated core vertical temperature structure, winds at different heights, vertical winds in and around the core, vorticity and divergence fields at the lower and upper levelsll support the characteristics of a mature storm. The model storm has moved towards the west of the observed track during the development phase although the location of the storm in the initial and final phases agreed with the observations. The simulated rainfall distribution associated with the storm agreed reasonably with observations.
    Sun Y., Z. Zhong, and W. Lu, 2015: Sensitivity of tropical cyclone feedback on the intensity of the western Pacific subtropical high to microphysics schemes. J. Atmos. Sci.,72, 1346-1368, doi: 10.1175/JAS-D-14-0051.1.10.1175/JAS-D-14-0051.1ae6dd228dc51a36d43a89ef3c3f3a91fhttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2015JAtS...72.1346Shttp://adsabs.harvard.edu/abs/2015JAtS...72.1346SNot Available
    Tao, W-K., J. J. Shi, S. S. Chen, S. Lang, P.-L. Lin, S.-Y. Hong, C. Peters-Lidard, A. Hou, 2011: The impact of microphysical schemes on hurricane intensity and track. Asia-Pacific Journal of Atmospheric Sciences.,47, 1-16, doi: 10.1007/ s13143-011-1001-z.
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    Wang Y. Q., 2009: How do outer spiral rainbands affect tropical cyclone structure and intensity? J. Atmos. Sci.,66, 1250-1273, doi: 10.1175/2008JAS2737.1.10.1175/2008JAS2737.1cd8d5604045d66cacadd3ba570056c28http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2009JAtS...66.1250Whttp://adsabs.harvard.edu/abs/2009JAtS...66.1250WThe numerical results show that cooling in the outer spiral rainbands maintains both the intensity of a tropical cyclone and the compactness of its inner core, whereas heating in the outer spiral rainbands decreases the intensity but increases the size of a tropical cyclone. Overall, the presence of strong outer spiral rainbands limits the intensity of a tropical cyclone. Because heating or cooling in the outer spiral rainbands depends strongly on the relative humidity in the near-core environment, the results have implications for the formation of the annular hurricane structure, the development of concentric eyewalls, and the size change in tropical cyclones.
    Wang Y. Q., 2012: Recent research progress on tropical cyclone structure and intensity. Tropical Cyclone Research and Review,1, 254-275, doi: 10.6057/2012TCRR02.05.10.6057/2012TCRR02.057ed263920a31ed30cd64f5dff29182f3http%3A%2F%2Fwww.researchgate.net%2Fpublication%2F273123335_recent_research_progress_on_tropical_cyclone_structure_and_intensityhttp://www.researchgate.net/publication/273123335_recent_research_progress_on_tropical_cyclone_structure_and_intensityABSTRACT This article provides a balanced, brief review on the research progress in the area of tropical cyclone (TC) structure and intensity achieved in the past three decade. Efforts have been made to introduce basic concepts and new findings relevant to the understanding of TC structure and intensity in ways as simple and appreciate as possible. After a brief discussion on the axisymmetric and asymmetric structure of mature TCs, progress in our understanding of spiral rainbands, concentric eyewall cycle, annular hurricane structure, and the inner-core size of TCs is highlighted. This is followed by discussions on the maximum potential intensity (MPI) of TCs and factors that limit TC maximum intensity. Some important remaining issues that need to be studied and addressed in the near future by the research community are identified and briefly discussed as well
    Xu J., Y. Q. Wang, 2010a: Sensitivity of tropical cyclone inner-core size and intensity to the radial distribution of surface entropy flux. J. Atmos. Sci.,67, 1831-1852, doi: 10.1175/2010JAS3387.1.10.1175/2010JAS3387.107165f5203754efb3a29593130bc66behttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2010JAtS...67.1831Xhttp://adsabs.harvard.edu/abs/2010JAtS...67.1831XNot Available
    Xu J., Y. Q. Wang, 2010b: Sensitivity of the simulated tropical cyclone inner-core size to the initial vortex size. Mon. Wea. Rev.,138, 4135-4157, doi: 10.1175/2010MWR3335.1.10.1175/2010MWR3335.17e1dc9ac5a702cd3bf40a1dcb34985e7http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2010MWRv..138.4135Xhttp://adsabs.harvard.edu/abs/2010MWRv..138.4135XThe relative importance of the initial vortex size and the environmental relative humidity (RH) to the TC inner-core size is also evaluated. It is found that the inner-core size of the simulated storm at the mature stage depends more heavily on the initial vortex size than on the initial RH of the environment.
    Yang M.-J., L. Ching, 2005: A modeling study of Typhoon Toraji (2001): Physical parameterization sensitivity and topographic effect. Terrestrial, Atmospheric and Oceanic Sciences, 16, 177- 213.10.1080/095373205000447768cd65b09-d760-4374-901c-aea33761bfb2468b70bb2a73c394a0bf933eaf9be216http%3A%2F%2Fwww.researchgate.net%2Fpublication%2F285737401_A_modeling_study_of_Typhoon_Toraji_2001_Physical_parameterization_sensitivity_and_topographic_effectrefpaperuri:(faba0c64f640694b4efc428735dd2494)http://www.researchgate.net/publication/285737401_A_modeling_study_of_Typhoon_Toraji_2001_Physical_parameterization_sensitivity_and_topographic_effectThis paper investigates the dependence of simulated track, central pressure, maximum wind, and accumulated rainfall of Typhoon Toraji (2001) on physical parameterizations, using the fifth-generation Pennsylvania State University- National Center for Atmospheric Research Mesoscale Model (MM5). The model configuration includes three nested domains with grid size of 60, 20, and 6.67 km, respectively. Three sets of five numerical experiments on cumulus, cloud microphysics, and planetary boundary layer (PBL) parameterizations are performed (15 experiments totally). Among subgrid-scale cumulus schemes tested, the simulated typhoon with the Grell scheme has the best track. For grid-scale cloud microphysics scheme examined, all storms have similar tracks, with the best simulated track using, the Goddard Graupel cloud microphysics scheme. The PBL parameterization substantially affects the simulated typhoon tracks, and the storm with the Medium-Range Forecast model PBL has track and intensity that most resemble actual observations. An experiment with the best scheme from each of three sets of physical parameterization experiments has the best performance in terms of central pressure, maximum wind and accumulated rainfall; it can simulate the westward turning of Toraji's track right before the landfall. Standard deviation and ensemble (arithmetic) mean are calculated for each set of physical parameterization experiments. The ensemble-mean track and rainfall distribution are much closer to the observations than each individual experiment. A combination of the topographically- and environmentally-induced vertical moisture fluxes, calculated based on the flux model of Lin et al. (2001), corresponded well to the hourly surface rainfall distribution. An analysis of nondimensional parameters for typhoon's track continuity over the Taiwan island shows that Typhoon Toraji's track discontinuity is consistent with the control parameter analysis proposed by Lin et al. (2002). The westward turning of Toraji's track right before the landfall may be caused by horizontal advection process due to flow blocking, on the basis on a momentum budget analysis.
    Yuan J. N., X.D. Wang, Q.L. Wan, and C.X. Liu, 2007: A 28-year climatological analysis of size parameters for Northwestern Pacific tropical cyclones. Adv. Atmos. Sci.,24, 24-34, doi: 10.1007/s00376-007-0024-y.10.1007/s00376-007-0024-y66067ade2ea97aa0f7f74fe981c917a2http%3A%2F%2Flink.springer.com%2F10.1007%2Fs00376-007-0024-yhttp://d.wanfangdata.com.cn/Periodical_dqkxjz-e200701003.aspx正A 28-year best track dataset containing size parameters that include the radii of the 15.4 m s-1 winds (R15) and the 25.7 ms-1 winds (R26) of tropical cyclones (TCs) in the Northwestern Pacific, the NCEP/ NCAR reanalysis dataset and the Extended Reconstructed Sea Surface Temperature (ERSST) dataset
    Zhang C. X., Y.Q. Wang, and K. Hamilton, 2011: Improved representation of boundary layer clouds over the southeast Pacific in ARW-WRF using a modified Tiedtke cumulus parameterization scheme. Mon. Wea. Rev.,139, 3489-3513, doi: 10.1175/MWR-D-10-05091.1.
    Zhu T., D.-L. Zhang, 2006: The impact of the storm-induced SST cooling on hurricane intensity. Adv. Atmos. Sci.,23, 14-22, doi: 10.1007/s00376-006-0002-9.10.1007/s00376-006-0002-91267dc5780c303278f5f8c9e3bbac10ehttp%3A%2F%2Flink.springer.com%2F10.1007%2Fs00376-006-0002-9http://d.wanfangdata.com.cn/Periodical_dqkxjz-e200601002.aspxThe effects of storm-induced sea surface temperature (SST) cooling on hurricane intensity are investigated using a 5-day cloud-resolving simulation of Hurricane Bonnie (1998). Two sensitivity simulations are performed in which the storm-induced cooling is either ignored or shifted close to the modeled storm track. Results show marked sensitivity of the model-simulated storm intensity to the magnitude and relative position with respect to the hurricane track. It is shown that incorporation of the storm-induced cooling, with an average value of 1.3℃, causes a 25-hPa weakening of the hurricane, which is about 20hPa per 1℃ change in SST. Shifting the SST cooling close to the storm track generates the weakest storm,accounting for about 47% reduction in the storm intensity. It is found that the storm intensity changes are well correlated with the air-sea temperature difference. The results have important implications for the use of coupled hurricane-ocean models for numerical prediction of tropical cyclones.
    Zou X. L., Q. N. Xiao, 2000: Studies on the initialization and simulation of a mature hurricane using a variational bogus data assimilation scheme. J. Atmos. Sci.,57, 836-860, doi: 10.1175/1520-0469(2000)057<0836:SOTIAS>2.0.CO;2.a84be4c28d911ad2c57496a3f1da2ad9http%3A%2F%2Fadsabs.harvard.edu%2Fcgi-bin%2Fnph-data_query%3Fbibcode%3D2000JAtS...57..836Z%26db_key%3DPHY%26link_type%3DABSTRACT%26high%3D03937http://xueshu.baidu.com/s?wd=paperuri%3A%28d0b04ba5bcc8a68e79b6748914ca3898%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Fadsabs.harvard.edu%2Fcgi-bin%2Fnph-data_query%3Fbibcode%3D2000JAtS...57..836Z%26db_key%3DPHY%26link_type%3DABSTRACT%26high%3D03937&ie=utf-8&sc_us=5902252888408546344
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Manuscript received: 17 August 2015
Manuscript revised: 19 April 2016
Manuscript accepted: 27 April 2016
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Sensitivity of the Simulation of Tropical Cyclone Size to Microphysics Schemes

  • 1. School of Energy and Environment, City University of Hong Kong, Hong Kong

Abstract: The sensitivity of the simulation of tropical cyclone (TC) size to microphysics schemes is studied using the Advanced Hurricane Weather Research and Forecasting Model (WRF). Six TCs during the 2013 western North Pacific typhoon season and three mainstream microphysics schemes-Ferrier (FER), WRF Single-Moment 5-class (WSM5) and WRF Single-Moment 6-class (WSM6)-are investigated. The results consistently show that the simulated TC track is not sensitive to the choice of microphysics scheme in the early simulation, especially in the open ocean. However, the sensitivity is much greater for TC intensity and inner-core size. The TC intensity and size simulated using the WSM5 and WSM6 schemes are respectively higher and larger than those using the FER scheme in general, which likely results from more diabatic heating being generated outside the eyewall in rainbands. More diabatic heating in rainbands gives higher inflow in the lower troposphere and higher outflow in the upper troposphere, with higher upward motion outside the eyewall. The lower-tropospheric inflow would transport absolute angular momentum inward to spin up tangential wind predominantly near the eyewall, leading to the increment in TC intensity and size (the inner-core size, especially). In addition, the inclusion of graupel microphysics processes (as in WSM6) may not have a significant impact on the simulation of TC track, intensity and size.

1. Introduction
2. Model configuration and experimental design
  • The Advanced Hurricane Weather Research and Forecasting Model (WRF, known also as AHW), version 3.6, is employed to simulate six TCs in the 2013 western North Pacific typhoon season. They are: Soulik, Usagi, Danas, Wipha, Francisco and Haiyan. These six cases are chosen because they had a lifetime of more than three days, reached hurricane force at least once during their lifetime, and their tracks were diverse enough to represent the general spread of tracks over the western North Pacific (Fig. 1). The same typhoon season is chosen so as to minimize the uncertainty from different data assimilation techniques used in different years. All six TC cases have different initial size. Note also that six cases are used in this study, rather than a single case, because this could increase the robustness of the conclusions.

    Figure 1.  Summary of TC tracks with different microphysics schemes in different TC cases.

    The model domain is triple-nested with two-way interactive nesting and with the inner meshes automatically vortex-following. The horizontal grid resolutions are 36, 12 and 4 km, and the corresponding domain sizes are 9360× 6840, 1440× 1440 and 840× 840 km2, respectively. The outermost static domain is centered at (23.5°N, 140°E), which is broad enough to cover all the TC cases and the western North Pacific. The model has 36 vertical eta (η) levels, with higher vertical resolution in the planetary boundary layer, and the reference model top pressure is 20 hPa. Complex topography and land-sea contrast are included. The initial and lateral boundary conditions are respectively initialized and six-hourly updated from the NCEP Final Operational Global Analysis data [FNL; 1° (lat) ×1° (lon)].

    For the model physics, the unified Noah land surface model (Tewari et al., 2004), MM5 (The PSU/NCAR mesoscale model) similarity surface layer physics (Jimènez et al., 2012) and Yonsei University (YSU) planetary boundary layer scheme (Hong and Lim, 2006) are employed. The Rapid Radiative Transfer Model for general circulation models (RRTMG) radiation scheme (Iacono et al., 2008) is taken to model the shortwave and longwave radiation physics. The Tiedtke cumulus parameterization scheme (Tiedtke, 1989; Zhang et al., 2011) is used for the outer two domains (36 and 12 km) only. To be more in line with recent research results regarding tropical storms and hurricanes, the modified surface bulk drag (Donelan et al., 2004) and enthalpy coefficients (Brutsaert, 1975) are applied in all domains.

    Three mainstream microphysics schemes that are widely used in the community——Ferrier (FER; simple three-class ice; Rogers et al., 2001), WRF Single-Moment five-class (WSM5; two-class ice; Hong et al., 2004), and WRF Single-Moment six-class (WSM6; three-class ice; Hong and Lim, 2006)——are employed for the sensitivity tests in this study. FER is currently an operational microphysics scheme in NCEP models, and is a simple and efficient scheme with diagnostic mixed-phase (ice, snow and graupel) processes, while the phase processes are all distinct in WSM5 and WSM6. The major difference between the WSM5 and WSM6 schemes is that the WSM6 scheme includes additional microphysics processes related to graupel. All other physical schemes and model settings are the same in all the experiments. More details of WRF physics and dynamics can be found in (Skamarock et al., 2008). Results from 18 experiments in total (six TC cases with three microphysics schemes) are compared to examine how the microphysics scheme affects the simulation of TC size.

    The model configuration and experimental design of the present study are summarized in Table 1. The details of the six TC simulations are listed in Table 2. To minimize the uncertainty and influence of other factors that can affect or be affected by TC track on the TC size, e.g. the environmental synoptic flow around a TC (Chan and Chan, 2013) and the planetary vorticity (Chan and Chan, 2014), the first 72 hours of model results are mainly discussed in this study. Results within the first three days should be largely representative because the mean track error at 72 h (T72) of the simulations is 170 km (i.e. 1.5° latitude), which is largely acceptable. The best-track data used in this study are based on those from the Joint Typhoon Warning Center.

3. Results
  • Previous studies have suggested that synoptic flows around a TC (e.g. Liu and Chan, 2002; Chan and Chan, 2013) and the TC inner-core-induced intensification (e.g. Chan and Chan, 2014) can affect TC size, which imply that TC track and intensity should also be examined when examining TC size. Hence, the impacts of the microphysics schemes on the simulations of TC track, intensity and size are discussed simultaneously.

  • Consistent with the findings from many previous studies (e.g. Yang and Ching, 2005; Zhu and Zhang, 2006; Li and Pu, 2008; Tao et al., 2011), the simulated TC tracks are not sensitive to the microphysics schemes (Fig. 1) in general, especially in the first 72 h when the TCs are over the open ocean where the influence of the landmass and topography on TC track is limited. This result suggests that the choice of the microphysics scheme among FER, WSM5 and WSM6 is likely not important in simulating the subtropical high in the early simulation, as the latter is a main factor in steering the TC.

  • The trends of the simulated TC intensity largely agree with the best-track data in the first 72 h, but the minimum sea-level pressure (MSLP) is generally higher than observed [20 hPa higher at 48 h of simulation (T48) on average; not shown]. As the main objective of this study is to investigate the impacts of microphysics schemes on the simulation of TC size, the difference between the simulated and observational TC intensity is not examined further. Instead, the comparisons among the three schemes on their simulations of TC intensity are discussed below.

    The model results suggest that the simulated TC intensity can be influenced by the choice of microphysics scheme. The TCs in the simulations with the WSM5 and WSM6 schemes are found to have lower MSLP than those with the FER scheme during the first 72 h in general (Fig. 2a). A higher maximum wind is attained for the TCs with the WSM6 scheme on average (Fig. 2b). For example, for Soulik, the WSM5 and WSM6 schemes give lower MSLP than that from the FER scheme throughout the entire simulation (Fig. 3a) although the differences in maximum wind are not that obvious in this case (Fig. 3b). The azimuthally averaged lower-tropospheric inflow and upper-tropospheric outflow between 25 and 48 h in the simulations with the WSM5 and WSM6 schemes are generally higher than those with the FER scheme (Fig. 4). (Chan and Chan, 2013) found that the change in TC intensity is positively related to the change in the upper-level angular momentum export, while the change in TC size is positively proportional to the change in the lower-tropospheric angular momentum import. (Chan and Chan, 2015b) further showed that the inner-core induced intensification is favorable for size growth. Inner-core induced intensification mainly results from the inner-core dynamics: for example, an increase in upper-tropospheric outflow leads to a decrease in surface pressure, and thus it favors the lower-tropospheric inflow near the inner core so that more angular momentum is transported towards the vortex center and consequently yields an expansion of horizontal wind fields.

    All the six TC cases in this study possess inner-core-induced intensification in the early simulation. The stronger upper-tropospheric outflow found in the simulations with WSM5 and WSM6 may be attributable to the greater diabatic heating generated outside the eyewall in the rainbands (Fig. 5). (Wang, 2009), (Fudeyasu and Wang, 2011) and (Wang, 2012) suggested that greater diabatic heating in rainbands gives higher inflow in the lower troposphere and higher outflow in the upper troposphere (Fig. 4), with higher upward motion (Fig. 6) outside the eyewall. The lower-tropospheric inflow would transport absolute angular momentum inward to spin up tangential wind predominantly near the eyewall (Fig. 7), leading to the increase in TC intensity and size (see TC size definition and details of the sensitivity of TC size to microphysics in sections 3.3 and 3.4). This is consistent with the convection such that more precipitation is found for TCs using the WSM5 and WSM6 schemes (Fig. 8). All these results imply that the WSM5 and WSM6 schemes could drive a stronger secondary circulation than the FER scheme and therefore result in a higher TC intensity. Such circumstances are also generally found in other cases and therefore not shown.

    Figure 2.  Differences among the microphysics schemes for (a) MSLP and (b) maximum wind in the first 72 h of six TC simulations. Black asterisks, blue triangles and red dots are the spreads of differences between WSM5 and FER, WSM6 and WSM5, and WSM6 and FER from the 6 TC simulations, respectively. Black solid, blue dash-dotted and red dashed lines indicate their means, respectively.

    Figure 3.  Time-series of (a) MSLP and (b) maximum wind of Soulik with different microphysics schemes.

    Figure 4.  Radius-height plots of the 24-h averaged azimuthal mean radial wind (units: m s$^-1$) between T25 and T48 in the case of Soulik among the (a) FER, (b) WSM5 and (c) WSM6 microphysics schemes. Negative and positive values indicate inflow and outflow, respectively. Panels (d-f) are the differences of the results shown in (a-c); see the titles of the plots for details of the subtractions. Note that the contour scales between (a-c) and (d-f) are different.

    Figure 5.  As in Fig. 4 but for diabatic heating (units: K s$^-1$) due to microphysics. In (a-c), negative and positive values indicate absorption and generation, respectively.

    Figure 6.  As in Fig. 4 but for vertical wind (units: m s$^-1$). In (a-c), negative and positive values indicate downward and upward motions, respectively.

    Figure 7.  As in Fig. 4 but for tangential wind (units: m s$^-1$). In (a-c), negative and positive values indicate cyclonic and anticyclone flows, respectively.

    Figure 8.  Radius-time plots of 24-h averaged azimuthal mean precipitation (units: mm h$^-1$) between T25 and T48 in the case of Soulik among the (a) FER, (b) WSM5 and (c) WSM6 microphysics schemes. Panels (d-f) are the differences of the results shown in (a-c); see the titles of the plots for details of the subtractions. Note that the contour scales between (a-c) and (d-f) are different.

  • An important result of this study is that TCs in the simulations with the WSM5 and WSM6 schemes are found to be generally larger than those with the FER scheme during the first 72 h of the simulation (Fig. 9). This suggests the selection of microphysics scheme can lead to differing simulations of TC size. In the early simulation, vortices can be assumed to experience almost the same environmental influence (as evidenced from section 3.1) so that the effects of the peripheral synoptic flows, environmental humidity and planetary vorticity (e.g. Liu and Chan, 2002; Hill and Lackmann, 2009; Chan and Chan, 2013, 2014) on the TC size difference might be negligible. Therefore, the factor or factors leading to such size differences likely relate to the inner-core microphysics processes.

    Figure 9.  Differences among the microphysics schemes of (a) R17 and (b) R25 in the first 72 h of six TC simulations. Black asterisks, blue triangles and red dots are the spreads of differences between WSM5 and FER, WSM6 and WSM5, and WSM6 and FER from the six TC simulations, respectively. Black solid, blue dash-dotted and red dashed lines indicate their means, respectively.

    The inner- and outer-core sizes in this study are defined as the azimuthal mean radius of storm-force (25 m s-1; R25) and gale-force (17 m s-1; R17) 10-m winds from the TC center, respectively. Figure 9 shows that the mean values of the differences among different microphysics schemes in R17 and R25 are similar. This means that the percentage difference of R25 is higher than that of R17 because R17 is about two to three times larger than R25 in general, which is given from the climatology. This is expected because, apart from the surface friction and upper-tropospheric divergence, the lower-tropospheric inflow can also be triggered by the diabatic heating through the inner-core-induced intensification (section 3.2). Such an intensification process would consequently lead to the decrease in surface pressure and enhance the lower-tropospheric inflow near the inner core such that absolute angular momentum is transported inward to expand the horizontal wind field, leading to the increase in TC size. The strongest lower-tropospheric inflow (e.g. Figs. 4a-c) and the maximum lower-tropospheric inflow difference (e.g. Figs. 4d and e) are therefore found somewhere within the inner core. The lower-tropospheric inflow then decreases radially such that its enhancements when using the WSM5 and WSM6 schemes are very small in the outer-core region. These results imply that the inner-core size is much more sensitive to the choice of microphysics scheme (among FER, WSM5 and WSM6) when comparing to the outer-core size.

  • (Sun et al., 2015) recently examined the sensitivity of the track of Typhoon Megi (2010) to the WSM3, Lin, WSM6 and Thompson microphysics schemes. They found that the microphysics could affect the activity of the subtropical high and potentially affect the track. This somehow contradicts what we have found in this study, as well as the findings of some other studies (Yang and Ching, 2005; Zhu and Zhang, 2006; Li and Pu, 2008; Tao et al., 2011). It therefore remains unclear as to whether TC track is sensitive to the choice of microphysics scheme. More studies are needed.

    On the other hand, the choice of microphysics scheme is found to be important in the simulation of TC intensity and size. The WSM5 and WSM6 schemes give a higher TC intensity and a larger size than the FER scheme in general, because they can give higher diabatic heating outside the eyewall in the rainbands, which consequently drives a stronger secondary circulation. To investigate why this is the case, the diabatic heating due to the microphysics processes is diagnosed. The model results coherently show that stronger diabatic heating is found within a 200 km radius from the TC center with the WSM5 and WSM6 schemes (e.g. Fig. 5). The more diabatic heating is generated, the higher the potential for the air parcel to move upward. Part of the moisture condenses and falls as precipitation, but most of the air continues to rise to the upper troposphere and results in stronger upper-tropospheric divergence. Such effects then enhance the lower-tropospheric inflow, and hence favor an increase in TC intensity and a growth in size (especially the inner-core size), because of the concept of the conservation of absolute angular momentum (Wang, 2009; Fudeyasu and Wang, 2011; Wang, 2012; Chan and Chan, 2013). Indeed, this is a kind of Sawyer-Eliassen balance (Bui et al., 2009). In addition, the present result evidences that the diabatic heating in the rapid filamentation zone mainly contributes to the increase in inner-core size, as revealed in Li et al. (2014, 2015), because the diabatic heating in the rapid filamentation zone (approximately 60-160 km from the TC center) is stronger in WSM5 and WSM6 than that in FER. Note that because the lower-tropospheric inflow that resulted from the inner-core-induced intensification decreases radially, more diabatic heating in the inner core does not necessarily lead to larger outer-core size if R17 is much larger than the radius of maximum wind (RMW).

    Figure 10.  Radius-height plots of the difference in 24-h averaged azimuthal mean (a) cloud water mixing ratio, (b) rain mixing ratio, and (c) ice condensate mixing ratio between T25 and T48 in the case of Soulik among the WSM5 and FER schemes. Units: dimensionless (g kg$^-1$).

    To understand why more diabatic heating is generated in the WSM5 and WSM6 schemes than in the FER scheme, the hydrometeor distributions (especially ice, snow, graupel and rain) and microphysics processes among these three schemes are investigated. Compared with the simulations from the FER scheme, those using the WSM5 and WSM6 schemes have less cloud water (e.g. Fig. 10a), more rain (e.g. Fig. 10b), and more ice condensate (ice/snow/graupel; e.g. Fig. 10c) mixing ratios in the region with stronger diabatic heating (e.g. cf. Figs. 5 and 10). This suggests the microphysics processes of autoconversion, freezing and accretion of cloud water by rain, snow and/or graupel, as well as the deposition of ice and snow, are stronger in the WSM5 and WSM6 schemes. Therefore, the WSM5 and WSM6 schemes result in more diabatic heating generation than the FER scheme. The detailed calculation comparisons of the microphysics processes among the schemes are not explicitly discussed in this study because they involve a lot of different empirical parameterizations, assumptions, simplifications etc. (see Rogers et al., 2001; Hong et al., 2004; Hong and Lim, 2006 for details). A more comprehensive discussion of these is beyond the scope of this paper.

    In addition, the diabatic heating difference between the simulations with the WSM5 and WSM6 schemes are found to be small and uneven in general (e.g. Fig. 5f). This is likely due to the small contribution of the graupel processes to the total heating, such that there is no significant intensity and size deviations among the cases (cf. the WSM5 and WSM6 schemes in Figs. 2 and 9). The results of this study could therefore suggest that the TC intensity and size (both R17 and R25) may not be sensitive to the inclusion of graupel microphysics processes. More work is needed to verify this in the future.

    Note that similar results are also found in the other five TC cases, and are therefore not discussed in detail in this study. However, caution should be exercised insofar as that although consistent results are found, they may not be universally applicable due to the limited testing (six TC cases in this study). In order to conduct a quantitatively significant investigation, more experiments, and TC cases, are needed. This study should be treated as a first step toward showing the potential impacts of three mainstream microphysics schemes on the simulated TC size.

4. Conclusions and discussion
  • The impacts of the choice of microphysics scheme on the simulation of TC size are studied using the Advanced Hurricane WRF model. Six TCs in the 2013 western North Pacific typhoon season and three mainstream microphysics schemes-FER, WSM5 and WSM6-are investigated. The inner- and outer-core sizes are defined as the azimuthal mean radius of storm-force (25 m s-1; R25) and gale-force (17 m s-1; R17) 10-m winds from the TC center, respectively. All the results (18 experiments in total) consistently show that the simulated TC track is not sensitive to these three microphysics schemes, which is consistent with results from previous studies. On the other hand, the simulated TC intensity and inner-core size are found to be significantly influenced by the choice of microphysics scheme. The simulated TC intensity and size (both R17 and R25) are similar in the simulations using the WSM5 and WSM6 schemes, and both are higher and larger than those using the FER scheme. The WSM5 and WSM6 schemes are shown to generate more diabatic heating then the FER scheme, which could be the main reason for such results. More diabatic heating could lead to higher upward motion, and hence result in higher upper-tropospheric divergence, lower-tropospheric convergence and precipitation rate. This consequently induces higher inflows at the lower troposphere and gives higher TC intensity and larger size (the inner-core size especially). It is important to note that this is a six-case sensitivity study, so the conclusions drawn should be more reliable than those from single case studies. This paper is helpful for explaining the impacts of various mainstream microphysics schemes on the simulation of TC track, intensity and, particularly, size.

    The sensitivity of three mainstream cumulus parameterizations [Kain-Fritsch (Kain, 2004), Tiedtke (Tiedtke, 1989; Zhang et al., 2011), and New Simplified Arakawa-Schubert (Han and Pan, 2011)] on TC size has also been examined (not shown because it is not the focus of this study). The simulated TC track, intensity and size are found to be insensitive to such cumulus parameterizations in the first 72 h of simulation in general. In addition, comparing the relative importance of the microphysics schemes and cumulus parameterizations, the impacts of microphysics schemes on the simulated TC size are higher than those from the cumulus parameterizations.

    Note again that the objective of the present study is not to search for the "best" microphysics scheme or matrix for TC prediction in WRF, although it is undoubtedly important. Many more numerical experiments and sensitivity tests have to be carried out in order to achieve this, and this is left for future work. Moreover, although the radiative forcing is likely an important factor in TC track, intensity and size (Fovell et al., 2010; Bu et al., 2014), the objective of this study was not to investigate different radiation schemes or the coupling between the microphysics scheme and the radiation scheme. The idea of this study was that, given the same radiation scheme, different microphysics schemes might give different simulations of intensity and size because of the heating that is generated being different in different schemes. It is possible that different radiation schemes could negate or enhance such heating, but this is not the point of the present paper.

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